Processing facilities are often managed using process control systems. Example processing facilities include manufacturing plants, chemical plants, crude oil refineries, ore processing plants, power plants, and paper or pulp manufacturing and processing plants. Among other operations, process control systems typically manage the use of motors, valves, and other industrial equipment in the processing facilities. In conventional process control systems, controllers are often used to control the operation of industrial equipment in the processing facilities. The controllers could, for example, monitor the operation of the industrial equipment, provide control signals to the industrial equipment, and generate alarms when malfunctions are detected.
In a controller using model predictive control (MPC) technology, at least one manipulated variable (MV) is used to keep at least one controlled variable (CV) at or near a setpoint (MPC.SP) or between high and low limits (MPC.LIMITS). For instance, an MPC controller could receive measurements of a temperature inside a reactor (a controlled variable) and attempt to keep the temperature at or near a setpoint by changing a cooling water flow (a manipulated variable) to a jacket of the reactor. The cooling water flow can be controlled by a downstream proportional-integral-derivative or “PID” controller, which could receive setpoint (SP) commands from the upstream MPC controller and process variable (PV) measurements of cooling water flow rate through a pipe and attempt to keep the flow rate at the commanded setpoint by changing a valve's opening (OP). The MPC controller can also adjust its manipulated variables to achieve an improved or maximum economic benefit. However, a manipulated variable cannot be changed indefinitely. The maximum amount that a manipulated variable can be changed is restricted by the physical limits of a process and its equipment or by operating limits of a downstream controller. In this document, an actual physical limit (APL) is defined as the most restrictive limit among all limits imposed, whether by a process, process equipment, or a downstream controller.
A user is often required to specify high and low operating limits for each manipulated variable. These limits define an admissible range in which the manipulated variable can be changed or “moved” by a controller. However, user-specified limits can gradually become stale or obsolete because the actual physical limits vary over time, such as due to process disturbances or changes or due to downstream controller configuration changes. An MPC controller may always assume that user-specified limits are achievable when determining an optimization solution for that variable, and optimization solutions for other manipulated variables can also be computed with that assumption. The MPC controller may therefore consistently push a downstream controller towards a seemingly-achievable limit until the downstream controller hits the actual physical limit and goes into a windup state. The physical or windup limit can be much closer to the manipulated variable's current value than the user-specified limit.
When this occurs, the MPC controller stops using the user-specified limit and begins using the actual physical limit. This often causes the optimization solution(s) to jump for the wound-up manipulated variable and all related manipulated variables. A downstream controller can also repeatedly go into and come out of windup, which can cause a number of complications. Over a longer period of time, for example, an optimization solution may jump back and forth because the limit that is actually used for optimization switches back and forth, and the user may observe unsettling zigzag movements as one or more downstream controllers (and thus their associated manipulated variables) go into and out of windup repeatedly. Also, as a downstream controller approaches windup or operates close to the windup state, its process variable (often denoted as PV in this document) may drift away from the desired setpoint, causing difficulties in predicting the effects of manipulated or disturbance variables on controlled variables and in determining how to configure the manipulated variables. In addition, since it is often not easy to predict the actual physical limit at which a downstream controller (and thus its associated manipulated variable) enters into windup, various makeshift solutions are often employed, which can produce mixed and inconsistent results.